Advances in Data Science and Adaptive Analysis最新文献_第8页

Novel Wrapper-Based Feature Selection for Efficient Clinical Decision Support System 基于包装的高效临床决策支持系统特征选择

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Advances in Data Science and Adaptive Analysis Pub Date : 2018-11-29 DOI: 10.1007/978-981-13-3582-2_9

R. Vanaja, S. Mukherjee

引用次数: 7

Linear and Nonlinear Analysis of Cardiac and Diabetic Subjects 心脏病和糖尿病受试者的线性和非线性分析

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Advances in Data Science and Adaptive Analysis Pub Date : 2018-11-29 DOI: 10.1007/978-981-13-3582-2_10

Ulka Shirole, Manjusha S. Joshi, Pritish K. Bagul

引用次数: 1

Statistical Characteristics of Long-Term High-Resolution Precipitable Water Vapor Data at Darwin 达尔文长期高分辨率可降水量数据的统计特征

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Advances in Data Science and Adaptive Analysis Pub Date : 2018-10-01 DOI: 10.1142/S2424922X18500109

Kimberly Leung, A. Subramanian, S. Shen

{"title":"Statistical Characteristics of Long-Term High-Resolution Precipitable Water Vapor Data at Darwin","authors":"Kimberly Leung, A. Subramanian, S. Shen","doi":"10.1142/S2424922X18500109","DOIUrl":"https://doi.org/10.1142/S2424922X18500109","url":null,"abstract":"This paper studies the statistical characteristics of a unique long-term high-resolution precipitable water vapor (PWV) data set at Darwin, Australia, from 12 March 2002 to 28 February 2011. To understand the convective precipitation processes for climate model development, the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) program made high-frequency radar observations of PWV at the Darwin ARM site and released the best estimates from the radar data retrievals for this time period. Based on the best estimates, we produced a PWV data set on a uniform 20-s time grid. The gridded data were sufficient to show the fractal behavior of precipitable water with Hausdorff dimension equal to 1.9. Fourier power spectral analysis revealed modulation instability due to two sideband frequencies near the diurnal cycle, which manifests as nonlinearity of an atmospheric system. The statistics of PWV extreme values and daily rainfall data show that Darwin’s PWV has El Nino Southern Oscillation (ENSO) signatures and has potential to be a predictor for weather forecasting. The right skewness of the PWV data was identified, which implies an important property of tropical atmosphere: ample capacity to hold water vapor. The statistical characteristics of this long-term high-resolution PWV data will facilitate the development and validation of climate models, particularly stochastic models.","PeriodicalId":47145,"journal":{"name":"Advances in Data Science and Adaptive Analysis","volume":"34 1","pages":"1850010:1-1850010:11"},"PeriodicalIF":0.6,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72940298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Multivariate Regression Reconstruction of the Quasi-Global Annual Precipitation on 1-Deg Grid From 1900 To 2015 1900 - 2015年1℃格网准全球年降水量的多元回归重建

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Advances in Data Science and Adaptive Analysis Pub Date : 2018-10-01 DOI: 10.1142/S2424922X18500080

L. Lämmlein, S. Shen

{"title":"A Multivariate Regression Reconstruction of the Quasi-Global Annual Precipitation on 1-Deg Grid From 1900 To 2015","authors":"L. Lämmlein, S. Shen","doi":"10.1142/S2424922X18500080","DOIUrl":"https://doi.org/10.1142/S2424922X18500080","url":null,"abstract":"This paper presents a multivariate linear regression reconstruction for the near-global annual precipitation anomalies with 1-deg latitude–longitude resolution from 1900 to 2015. The regression’s explanatory variables are the empirical orthogonal functions (EOFs), computed from the Global Precipitation Climatology Project (GPCP) dataset. The data for the regression’s dependent variable are from the station dataset of the Global Historical Climatology Network (GHCN). The data for the explanatory variables are the EOF data at the GHCN data locations. Compared to the earlier work of reconstruction at [Formula: see text] latitude–longitude resolution, our current reconstruction has two contributions. First, the spatial resolution is reduced to [Formula: see text] latitude–longitude. The finer resolution allows the data to be more useful in applications, such as historical drought assessment for a given region. Second, the multivariate regression is directly computed from linear regression models and hence includes the intercept term, which is not a coefficient of an EOF. The intercept enables a more realistic detection of the long-term trend of the spatial average. The trend of the global average annual precipitation from 1900 to 2015 is 0.133 (mm/day)/100a for the reconstruction with an intercept, and is 0.022 (mm/day)/100a without an intercept. The latter agrees with the trends of other models. The reconstruction error is assessed by a time-varying standard deviation.","PeriodicalId":47145,"journal":{"name":"Advances in Data Science and Adaptive Analysis","volume":"25 1","pages":"1850008:1-1850008:17"},"PeriodicalIF":0.6,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82573116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

The Odd Log-Logistic Log-Normal Distribution with Theory and Applications 奇对数- logistic对数-正态分布及其理论与应用

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Advances in Data Science and Adaptive Analysis Pub Date : 2018-10-01 DOI: 10.1142/S2424922X18500092

G. Özel, E. Altun, M. Alizadeh, Mahdieh Mozafari

引用次数: 2

Continuous Estimation Prediction of Knee Joint Angles Using Fusion of Electromyographic and Inertial Sensors for Active Transfemoral Leg Prostheses 主动经股腿假体中肌电与惯性传感器融合的膝关节角度连续估计与预测

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Advances in Data Science and Adaptive Analysis Pub Date : 2018-08-15 DOI: 10.1142/S2424922X18400089

A. Delis, C. Miosso, J. Carvalho, A. Rocha, G. Borges

引用次数: 7

Chaotic Dynamics in Brain Activity: An Approach Based on Cross-Prediction Errors for Nonstationary Signals 脑活动中的混沌动力学:基于非平稳信号交叉预测误差的方法

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Advances in Data Science and Adaptive Analysis Pub Date : 2018-08-15 DOI: 10.1142/S2424922X1840003X

B. Machado, André Fonseca, E. Morya, E. A. Júnior

引用次数: 0

Nonfatigating Brain-Computer Interface Based on SSVEP and ERD to Command an Autonomous Car 基于SSVEP和ERD的非疲劳脑机接口指挥自动驾驶汽车

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Advances in Data Science and Adaptive Analysis Pub Date : 2018-08-15 DOI: 10.1142/S2424922X18400053

Javier Castillo-Garcia, S. Muller, E. C. Bravo, T. Filho, A. D. Souza

引用次数: 1

Adaptive Spontaneous Brain-Computer Interfaces Based on Software Agents 基于软件代理的自适应自发脑机接口

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Advances in Data Science and Adaptive Analysis Pub Date : 2018-08-15 DOI: 10.1142/S2424922X18400041

Javier Castillo-Garcia, E. C. Bravo, T. Filho

引用次数: 1

Deep Learning of EEG Time-Frequency Representations for Identifying Eye States 脑电时频表征的深度学习用于眼状态识别

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Advances in Data Science and Adaptive Analysis Pub Date : 2018-08-15 DOI: 10.1142/S2424922X18400065

Dharmendra Gurve, S. Krishnan

引用次数: 9